Dynamic to static conversion of video data includes representing the dynamic media (video, animations) with a number of still images which carry selected important information within the dynamic media. For example, in the case of a video consisting of a pure pan or zoom sequence (i.e., global motion), the efficient representation may contain the beginning, middle and end frames of the pan or zoom. In the case of a commercial video consisting of short clips of different products manufactured by a company, the efficient representation may contain a single image from each product shown in the video. Although, it would be easy for an operator to find these images if the operator watched the whole video, such an editorial distillation is very time consuming. Accordingly, there is a substantial need for a method and system which can analyze dynamic media information in real time for purposes of selecting key frames acceptably representative of the dynamic media.
The subject invention is thus more particularly applicable to an improved real time selection method for a plurality of key frames from scenes comprising global motion within the dynamic video.
The key problem in selection of the key frames is to estimate the global motion between frames. Time domain global motion estimation techniques can be classified into three groups, feature correspondence methods, optical flow methods and direct methods. Feature correspondence requires a number of point correspondences among two or three frames to be known or estimated a priori. The motion parameters are computed from these correspondences. The other two methods do not require determination of distinct feature points, but instead utilize the optical flow constraint in between two corresponding views. The optical flow methods consist of two steps: the estimation of the optical flow field, and recovering the motion parameters using this estimated optical flow. On the other hand, direct methods utilize only the spatio-temporal image intensity gradients to estimate the motion. Many motion estimators in each of these categories have been proposed in the literature; however, all of these methods have some drawbacks and are exclusively designed for off-line computations. (J. Bergen, P. Hurt, R. Hingorani and S. Peleg, "A Three-Frame Algorithm for Estimating Two-Component Image Motion", IEEE Trans. Pattern Analy. Machine Intell, vol. 14, no.9, pp. 886-896, September 1992.)
The amount of data involved for identifying the particular values for all the pixel locations in a dynamic video makes any of the above prior art methods impractical for computing real time motion estimations for assessing representative static key frames for a dynamic video. Accordingly, there is also a need for a method that can reduce the necessary computation so that it can be done in real time and thereby avoid the disadvantages of delayed off-line computations.
The present invention contemplates a new and improved method and system which overcomes the above referenced problems and others to provide a new method for identification of a global motion in a dynamic video wherein the underlying computations can be accomplished in real time for the generation of a plurality of key static frames representative of the global motion portion of the video.